AtArpeely, we’ve developed some of the world’s most advanced advertising technology. Our machine learning (ML) media acquisition platform and “win-win” business model enables customers to bring highly intentful users to their offerings with precision, peace of mind and minimal overhead.
Real-time bidding is a dynamic and intricate process that involves buying and selling ad impressions in milliseconds. Each time a user opens an app or website, advertisers or ad-tech companies acting on behalf of advertisers have milliseconds to bid on ad spaces in real-time auctions, and the highest bidder wins the opportunity to display their ad. This is where Arpeely comes in, leveraging advanced algorithms, innovative UX and funnels to optimize the bidding process and maximize performance for advertisers.
At Arpeely, we use various signals often not used by traditional competitors to outperform the market and zero-down on high-intent and soon-to-be loyal users. For example, in advertising a mobile app, we predict, based on real-time conditions and user context, the user’s likelihood to make an in-app purchase many weeks into the future.
As for the ads themselves, gone are the days of simple banners; today’s ads are “mini products” that captivate and engage users. We employ a wide range of ad formats that go beyond industry standards. Our ads can be immersive videos, compelling messages, interactive experiences like mini-games or mini-apps, or even a multi-step mixture of all of the above. By integrating logic and interactivity, Arpeely enables users to engage with the ad content seamlessly and gauge user intent without leaving their main activity.
Our business model dictates that we don’t get paid if our advertiser doesn’t get paid. We like to say that our algorithms, like water, can trickle into hidden market opportunities missed by the rest of the industry that uses less granular tools. These and other capabilities make Arpeely a strategic partner in the challenging space of media and user acquisition.
Innovation at the edges of data science and engineering
Today, we handle millions of impressions per second and over a billion ML predictions daily. We are directly connected to seven of the world’s largest real-time bidding exchanges, including Google AdX. We also work very closely with our clients, ranging from prominent startups to companies in the S&P Top 20.
Daily, we tackle complex engineering and data challenges on multiple fronts. On the engineering side, we ensure that every real-time auction receives a lightning-fast response within a strict 150ms timeframe. On the data side, we fire multiple ML predictions per auction and ingest TBs of data daily. On the user-serving front, we serve A/B-tested assets across a long tail of geos and devices, with even the slightest fluctuations in load speeds affecting business dramatically.
Right from the start, we knew we couldn’t do it alone when it came to building our technology stack. When you look at available platforms, it’s clearGoogle Cloud has a robust architecture that is easy to manage, use and scale, especially for our use cases. They also have reliability and feature completeness which are critical in our line of business.
Under the hood
Building upon Google Kubernetes Engine (GKE), we run multiple services that handle our main bidding flows. We utilize Golang for services that run at a large scale and Python for when we prioritize development speed, community and readability. All of these can reach an immensely high scale, which is managed and monitored automatically in GKE. Communication between these services and our Redis (our Google Cloud partner) cluster happens in sub-millisecond latency over Google Cloud’s strong network infrastructure and enables us to run complex real-time logic for every impression.
Once we have tackled the actual bidding, we are left with the challenge of streaming our data into BigQuery for analytics and model training. We utilize a mix of Cloud Pub/Sub, Memorystore and Cloud Storage to create a mechanism capable of ingesting many TBs per day in near real-time without compromising on cost. Real-time data is critical for a company like Arpeely to test and reiterate at a fast pace.
BigQuery is our data warehouse for operational analysis and is an essential part of our business. We use it both as a warehouse, for large-scale computations and in an operational capacity that closes the loop between production, data, and ML retraining. A team of two or three people can manage petabytes at scale with minimal maintenance.
On top of these, we’ve built a state-of-the-art in-house model pipeline suited specifically for ad-tech industry purposes. It allows us to effectively deploy complex solutions — on-the-fly calibration, flexible conversion steps, sampling of heavily imbalanced data sets, adjusting weights, and A/B-tested model deployment and more.
Google Cloud also offers us an entry point for several very useful built-in products that have become deeply embedded in our daily stack and routine. Among them are Operations Suite (formerly Stackdriver), Cloud Profiler, Cloud Storage, Cloud CDN, Cloud SQL, Memorystore, Cloud Scheduler, Error Reporting, and more.
In addition to all the technology, there’s also a human touch. Google’s skilled Customer Success team possesses a unique blend of technical expertise and business acumen, acting as strategic advertisers and opening doors we did not know existed.
Opening the door to the future of advertising
Standardizing on Google Cloud enables us to focus our resources on innovation and growth. Instead of having to research business solutions and invest time integrating disparate technologies, we can tap into a wide range of Google Cloud tools as needed. Thus, it is crucial that we set up a good technological foundation and prepare for future growth of the business.
Google Cloud enables us to focus our resources on innovation rather than our infrastructure. This means we can put more effort into finding ways to match clients with high-value customers and grow their revenues. Even though online advertising has been around for over 20 years and pioneered by Google itself, Google Cloud gives us the impetus to disrupt the market and deliver greater levels of value to our customers today and in the future.
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